An Inductive Approach to Using Google Search Trends To Identify Attitudes and Areas of COVID-19 Vaccine Hesitancy

22 Pages Posted: 22 Jul 2021

See all articles by Doug Beeferman

Doug Beeferman

Massachusetts Institute of Technology (MIT)

Larry Au

Columbia University

Rima A. Abdul-Khalek

Faculty of Health Sciences, American University of Beirut

Angel Desai

International Society for Infectious Diseases

Maimuna S. Majumder

Boston Children's Hospital - Computational Health Informatics Program; Harvard University - Harvard Medical School

Date Written: June 28, 2021

Abstract

In this study, we present and apply a novel inductive approach that uses Google Search Trends data for public health surveillance of COVID-19 vaccine hesitancy from January to April 2021. In contrast to previous studies that use researcher-curated keywords, our study combed through over 2 million social media posts on Twitter to identify over 3,000 keywords related to vaccination, enabling us to capture potential sources of vaccine hesitancy that would otherwise be missed. These keywords were used to retrieve Google Search Trends for 774 queries that yielded nonzero search volumes for at least 45 U.S. states. We then used the CovidCast survey of vaccine acceptance at the U.S. state level to calculate a Spearman’s rank correlation coefficient for each term. Negatively correlated queries, we argue, can help shed light on potential sources of vaccine hesitancy. As noted by Flahault et al. (2020), in order to achieve “precision global health” and “real-time action”, researchers must creatively combine multiple data sources in order to deliver targeted interventions. We are hopeful that our approach will be useful for practitioners in addressing the problem of vaccine hesitancy.

Note: Funding: This work was supported in part by grant T32HD040128 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health.

Declaration of Interests: The authors declare that there is no conflict of interest.

Keywords: COVID-19, vaccine hesitancy, Google Search Trends, public health surveillance

Suggested Citation

Beeferman, Doug and Au, Larry and Abdul-Khalek, Rima A. and Desai, Angel and Majumder, Maimuna, An Inductive Approach to Using Google Search Trends To Identify Attitudes and Areas of COVID-19 Vaccine Hesitancy (June 28, 2021). Available at SSRN: https://ssrn.com/abstract=3875047 or http://dx.doi.org/10.2139/ssrn.3875047

Doug Beeferman

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Larry Au (Contact Author)

Columbia University ( email )

Suite 501, Knox Hall
606 W 122nd St
New York, NY 10027
United States

Rima A. Abdul-Khalek

Faculty of Health Sciences, American University of Beirut ( email )

Beirut, 0236
Lebanon

Angel Desai

International Society for Infectious Diseases ( email )

Brookline, MA

Maimuna Majumder

Boston Children's Hospital - Computational Health Informatics Program ( email )

United States

Harvard University - Harvard Medical School ( email )

25 Shattuck St
Boston, MA 02115
United States

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